Background

Remote sensing based on multispectral imaging may be useful for detecting vegetation stress responses in agriculture.

Objectives

To evaluate the potential of orbital multispectral imaging in discriminating the most effective strategies for reducing plant-parasitic nematode populations, thereby preventing yield losses in coffee production.

Methods

Coffee plants were treated with eleven treatments, including Bacillus spp. isolates, commercial biological products, commercial chemical nematicides, and water (control group). Initial and final nematode populations in the soil were quantified, and surface reflectance data were collected using the Planet orbital multispectral sensor. The data were classified using the random tree algorithm.

Results

The population of plant-parasitic nematodes was reduced by 35.90% and 55.13% following the application of B. amyloliquefaciens isolate B266 and B. subtilis isolate B33, respectively. Under the conditions of this experiment, multispectral imaging accurately discriminated the most nematicidal treatments, with a global accuracy of 80%.

Conclusions

Orbital multispectral imaging can discriminate the most effective treatments used for nematode management in coffee plants, highlighting its potential as a supportive tool in agriculture.

中文翻译：

---

轨道多光谱成像：区分咖啡线虫管理策略的工具

 背景

基于多光谱成像的遥感可能有助于检测农业中的植被胁迫反应。

 目标

评估轨道多光谱成像在辨别减少植物寄生线虫种群的最有效策略方面的潜力，从而防止咖啡生产中的产量损失。

 方法

咖啡树经过十一种处理，包括芽孢杆菌属。分离株、商业生物制品、商业化学杀线虫剂和水（对照组）。对土壤中的初始和最终线虫种群进行了量化，并使用行星轨道多光谱传感器收集了表面反射率数据。使用随机树算法对数据进行分类。

 结果

施用解淀粉芽孢杆菌B266和枯草芽孢杆菌B33后，植物寄生线虫数量分别减少了35.90%和55.13%。在本实验条件下，多光谱成像准确地区分了最具杀线虫效果的处理方法，总体准确度为 80%。

 结论

轨道多光谱成像可以区分用于咖啡植物线虫管理的最有效的治疗方法，突显其作为农业支持工具的潜力。